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The article announces the winners of Development's Outstanding Paper Prize for papers published in 2023. The winning papers focus on developmental and stem cell biology. One paper demonstrates the potential of genome engineering techniques and pharmacological upregulation of the Wnt signaling pathway in treating frizzled 2-associated congenital malformations in mouse models. Another paper explores how Frizzled2 receives WntA signaling during butterfly wing pattern formation, providing insights into the complexity and evolution of signaling pathways. The article also mentions a study on the development of primordial germ cell-like cells using stem cell technologies. Additionally, the article discusses a study on the molecular functioning of WntA in butterfly wing color patterning, which involved collaboration between international teams and faced challenges in rearing and injecting butterflies in the lab. The researchers plan to further investigate butterfly color patterns. [Extracted from the article]

This article features an interview with Jingjing Sun and Angelike Stathopoulos, who conducted a study on the collective migration of caudal visceral mesoderm (CVM) cells in Drosophila embryos. They discovered that cell division coordinates two gene expression programs in migrating CVM cells. The researchers discuss their scientific backgrounds and the questions they are trying to answer in their lab. They also highlight the importance of the Drosophila system for their research. The study's key findings include the identification of two groups of genes that regulate the behaviors of CVM cells during migration, and the role of cell division in controlling gene expression programs. The researchers also discuss their motivations and future directions for their research. [Extracted from the article]

A high mortality rate was found in cancer patients with distant metastasis. Development of targeted drugs for effectively inhibiting cancer metastasis is the key for increasing therapeutic success. In the current study, a folding paper system was developed to mimic a tumor–vascular interface for the study of long-distance cell migration. Correlation between the cell migration distance and metastasis-associated gene was successfully analyzed by disassembling the stacked paper construct. The result revealed that the migration distance and number of migrated cells were highly correlated to cell characteristics. Moreover, immunocytochemistry was directly conducted on the paper layer to study the signaling pathway. Kelch-like and protein tyrosine phosphatase families were examined and the PTPN13 gene was shown to regulate long-distance cell migration. By analyzing the phosphorylated mTOR, the PTPN13 gene was further confirmed to be a tumor suppressor gene that inhibits long-distance cell migration. The folding paper system provides an alternative approach for long-distance cell migration. Metastasis-associated gene expression can be analyzed to potentially develop targeted drugs for cancer metastasis inhibition. [ABSTRACT FROM AUTHOR]

Invasive paper wasps such as Polistes dominula are a major pest and problem for biodiversity around the globe. Safe and highly targeted methods for the control of these and other social wasp populations are needed. We attempted to identify potentially-lethal gene targets that could be used on adult paper wasps in a gene silencing or RNA interference (RNAi) approach. Double-stranded RNA (dsRNA) was designed to target genes for which silencing has proven lethal in other insects. dsRNA was provided either orally to foragers or directly injected into the wasps. We also provided the dsRNA unprotected or protected from degradation by gut nucleases in two different forms (lipofectamine and carbon quantum dots). The effects of oral delivery of 22 different gene targets to forager wasps was evaluated. The expression of five different genes was successfully reduced following dsRNA ingestion or injection. These gene targets included the FACT complex subunit spt16 (DRE4) and RNA-binding protein fusilli (FUSILLI), both of which have been previously shown to have potential as lethal targets for pest control in other insects. However, we found no evidence of significant increases in adult wasp mortality following ingestion or injection of dsRNA for these genes when compared with control treatments in our experiments. The methods we used to protect the dsRNA from digestive degradation altered gene expression but similarly did not influence wasp mortality. Our results indicate that while many of the same gene targets can be silenced and induce mortality in other insects, dsRNA and RNAi approaches may not be useful for paper wasp control. [ABSTRACT FROM AUTHOR]

They describe the structure of the MRN Complex and its function in double-strand break (DSB) repair and analyze the different germline alterations of the MRN complex genes in autosomal recessive syndromes, as well as the association between heterozygous germline alterations in these genes and cancer predisposition. In the rapidly evolving landscape of molecular genetics and genomics, this Special Issue brings together a collection of insightful review articles that delve into the forefront of scientific exploration. The authors also propose a possible explanation of the discrepancies in the published results of the effects of the OXTR gene polymorphisms and methylation on different diseases [[2]]. [Extracted from the article]

Despite significant advances in the diagnosis and treatment of cardiovascular diseases, recent calls have emphasized the unmet need to improve precision-based approaches in cardiovascular disease. Although some studies provide preliminary evidence of the diagnostic and prognostic potential of circulating coding and non-coding RNAs, the complex RNA biology and lack of standardization have hampered the translation of these markers into clinical practice. In this position paper of the CardioRNA COST action CA17129, we provide recommendations to standardize the RNA development process in order to catalyse efforts to investigate novel RNAs for clinical use. We list the unmet clinical needs in cardiovascular disease, such as the identification of high-risk patients with ischaemic heart disease or heart failure who require more intensive therapies. The advantages and pitfalls of the different sample types, including RNAs from plasma, extracellular vesicles, and whole blood, are discussed in the sample matrix, together with their respective analytical methods. The effect of patient demographics and highly prevalent comorbidities, such as metabolic disorders, on the expression of the candidate RNA is presented and should be reported in biomarker studies. We discuss the statistical and regulatory aspects to translate a candidate RNA from a research use only assay to an in-vitro diagnostic test for clinical use. Optimal planning of this development track is required, with input from the researcher, statistician, industry, and regulatory partners. [ABSTRACT FROM AUTHOR]

Paper mulberry vein banding virus (PMVBV), a member of the genus Badnavirus in the family Caulimoviridae, infects paper mulberry (Broussonetia papyrifera), a dicotyledonous plant. Putative promoter regions in the PMVBV genome were tested using recombinant plant expression vectors, revealing that the promoter activity of three genome fragments was about 1.5-fold higher than that of the 35S promoter of cauliflower mosaic virus in Nicotiana benthamiana. In transformed transgenic Arabidopsis thaliana plants, these promoter constructs showed constitutive expression. Based on the activity and gene expression patterns of these three promoter constructs, a fragment of 384 bp (named PmVP) was deduced to contain the full-length promoter of the PMVBV genome. The results suggest that the PMVBV-derived promoter can be used for the constitutive expression of transgenes in dicotyledonous plants. [ABSTRACT FROM AUTHOR]

RNA interference (RNAi) is a useful tool to assess gene function by knocking down expression of a target gene and has been used successfully in domestic and laboratory organisms. However, the use of RNAi for functional genomics has not fully extended into ecological model organisms in natural environments. Assessment of gene function in the wild is important because gene function can be environmentally and context dependent. Here, we present a case study using RNAi to assess gene function in wild paper wasps Polistes metricus, to test roles for two candidate genes ( NADH dehydrogenase ( NADHdh) and retinoid and fatty acid binding protein ( RfaBp)) in the development of reproductive castes. Previous studies have shown that these genes are upregulated in larvae that become queens compared to workers, but this pattern was reversed in the laboratory, making field-based studies necessary. We orally administered dsRNA to larvae in field colonies and found evidence of a short-term knockdown followed by a compensatory rebound in expression for RfaBp. We also observed the predicted worker-like decrease in lipid stores in NADHdh dsRNA treated wasps, suggesting a possible role for NADHdh in caste development. We discuss our results in the context of challenges for using RNAi for functional genomics in ecological model organisms in the field. [ABSTRACT FROM AUTHOR]

Why workers forfeit direct reproduction is a crucial question in eusocial evolution. Worker reproduction provides an excellent opportunity to understand the mechanism of kin conflict resolution between the queen and workers. We evaluated behavioral and physiological differences among females in the paper wasp Polistes chinensis antennalis to examine why some workers reproduce under queenright conditions. Reproductive workers were old and foraged less early in the season; their cuticular hydrocarbon (CHC) profiles overlapped with those of queens but were significantly different. The distinct CHC profile of the eggs of the queen likely represented a cue for policing against those by workers. Juvenile hormone (JH) and dopamine seemed to be associated with gonadotropic function, and the JH level of reproductive workers was similar to that of the queen. The high JH level of reproductive workers likely facilitated their reproduction even under queenright conditions. Gene expression levels of the queen and reproductive workers differed only in vitellogenin. These results suggest that worker reproduction is facilitated by an increase in JH level; however, CHC is not a fertility-linked signal, but a queen-linked signal; consequently, reproductive workers without a queen-linked signal might be allowed to stay within the colony. [ABSTRACT FROM AUTHOR]

The gut microbiota is recognized as having major impact in health and disease. Sample storage is an important aspect to obtain reliable results. Mostly recommended is immediate freezing, however, this is not always feasible. Faecal occult blood test (FOBT) papers are an appealing solution in such situations, and most studies find these to be applicable, showing no major changes within 7 days storage at room temperature (RT). As fieldwork often requires RT storage for longer periods, evaluation of this is warranted. We performed 16S rRNA gene sequencing of 19 paired faecal samples immediately frozen or kept five weeks and five months at RT on FOBT papers. Alpha-diversity evaluation revealed no effect of FOBT storage, and evaluation of beta-diversity showed that host explained 65% of community variation, while storage method explained 5%. Evaluation of community dispersion and the Firmicutes/Bacteroidetes ratio revealed a larger effect of storage time for fresh-frozen samples. Single taxa evaluation (order-to-genus level) showed significant alterations of four (of 37) genera after five weeks and five genera after five months. When comparing the two timepoints, alterations were only detectable for fresh-frozen samples. Our findings reveal that long term storage on FOBT papers is an applicable approach for microbiota research. [ABSTRACT FROM AUTHOR]

Few animals are known to individually recognize conspecifics, i.e. learn and recall unique individuals during subsequent encounters, and nearly all are social vertebrates. Remarkably, the social paper wasp Polistes fuscatus has recently been discovered to possess this ability, which is useful for remembering identities during competitive social interactions. We analyzed brain gene expression in staged encounters between pairs of individuals to explore potential mechanisms underlying wasps' ability to recall familiar individuals using real-time qRT-PCR. We identified four candidate genes ( IP3K, IP3R, Nckx30C and Su(var)2- 10) that were down-regulated in the presence of familiar individuals compared to single wasps and pairs of wasps meeting for the first time. These candidate genes are related to calcium signaling, therefore, we treated wasps with lithium chloride, a pharmacological agent that inhibits calcium signaling in neurons. This treatment decreased aggression in paper wasps, but did not affect expression of genes related to calcium signaling. The results suggest calcium signaling differences may be related to individual memory recall in wasps, and we present four promising candidate genes for future study. These data suggest genes associated with dominance behavior may be co-opted for individual recognition, but further work is needed to establish a causal association with the behavior. [ABSTRACT FROM AUTHOR]

Increasing cellulase production in cellulolytic fungus Trichoderma reesei is of interest for biofuels and biorefineries. Previous studies indicated that secreted protein was occasionally accumulated in vacuoles; this phenomenon has also been reported in T. reesei. Therefore, alleviating vacuolar transport seems to be a promising strategy for improving cellulase production in T. reesei. Herein, we found that knockout of vps10, vps13, and vps21, among 11 vacuolar protein sorting factors, improved cellulase production in T. reesei. The filter paper activity in Δvps10, Δvps13, and Δvps21 increased by 1.28-, 2.45-, and 2.11-fold than that of the parent strain. Moreover, the β-glucosidase activity in Δvps13 and Δvps21 increased by 3.22- and 3.56-fold after 6 days of fermentation. Furthermore, we also found that the vacuolar trafficking towards vacuoles was partially impaired in three knockout mutants, and disruption of vps13 alleviated the autophagy process. These results indicated that alleviated transport and degradation towards vacuole in Δvps10, Δvps13, and Δvps21 might improve cellulase production. Of note, the expression of cellulase genes in Δvps13 and Δvps21 was dramatically increased in the late induction phase compared to the parent. These results suggested that Vps13 and Vps21 might influence the cellulase production at transcription level. And further transcriptome analysis indicated that increased cellulase gene expression might be attributed to the differential expression of sugar transporters. Our study unravels the effect of alleviating vacuolar transport through knockout vps10, vps13, and vps21 for efficient cellulase secretion, providing new clues for higher cellulase production in T. reesei. Key points: • Disruption of vps10, vps13 or vps21 improves cellulase production • Vacuolar transport is impaired in three vps KO mutants • Deletion of vps13 or vps21 increases the transcript of cellulase genes in late stage [ABSTRACT FROM AUTHOR]

Diabetes alters the function of ion channels responsible for regulating arterial smooth muscle membrane potential, resulting in vasoconstriction. Our prior research demonstrated an elevation of TMEM16A in diabetic arteries. Here, we explored the mechanisms involved in Transmembrane protein 16A (TMEM16A) gene expression. Our data indicate that a Snail-mediated repressor complex regulates arterial TMEM16A gene transcription. Snail expression was reduced in diabetic arteries while TMEM16A expression was upregulated. The TMEM16A promoter contained three canonical E-box sites. Electrophoretic mobility and super shift assays revealed that the −154 nt E-box was the binding site of the Snail repressor complex and binding of the repressor complex decreased in diabetic arteries. High glucose induced a biphasic contractile response in pressurized nondiabetic mouse hindlimb arteries incubated ex vivo. Hindlimb arteries incubated in high glucose also showed decreased phospho-protein kinase D1 and TMEM16A expression. In hindlimb arteries from nondiabetic mice, administration of a bolus dose of glucose activated protein kinase D1 signaling to induce Snail degradation. In both in vivo and ex vivo conditions, Snail expression exhibited an inverse relationship with the expression of protein kinase D1 and TMEM16A. In diabetic mouse arteries, phospho-protein kinase D1 increased while Akt2 and pGSK3β levels declined. These results indicate that in nondiabetic mice, high glucose triggers a transient deactivation of the Snail repressor complex to increase arterial TMEM16A expression independently of insulin signaling. Conversely, insulin resistance activates GSK3β signaling and enhances arterial TMEM16A channel expression. These data have uncovered the Snail-mediated regulation of arterial TMEM16A expression and its dysfunction during diabetes. NEW & NOTEWORTHY: The calcium-activated chloride channel, TMEM16A, is upregulated in the diabetic vasculature to cause increased vasoconstriction. In this paper, we have uncovered that the TMEM16A gene expression is controlled by a Snail-mediated repressor complex that uncouples with both insulin-dependent and -independent pathways to allow for upregulated arterial protein expression thereby causing vasoconstriction. The paper highlights the effect of short- and long-term glucose-induced dysfunction of an ion channel expression as a causative factor in diabetic vascular disease. [ABSTRACT FROM AUTHOR]

Colorectal cancer is a malignant tumor with high morbidity and mortality worldwide. Histone lactylation, a new protein post-translational modification, can be used as a potential biomarker for the diagnosis and treatment of colorectal cancer by regulating the structure of chromatin and gene transcription. This paper focuses on the role and mechanism of histone lactylation modification in the development of colorectal cancer. Additionally, the latest research progress and clinical experimental results are presented. This paper further shows that histone lactylation manipulates gene expression by affecting nuclear transcription factors and other epigenetic modifications involved in various life processes and subsequently regulates cell physiological function, revealing its regulatory mechanism and the functions of related enzymes. The relationships between histone lactylation and energy metabolic pathways such as glycolysis and oxidative phosphorylation are discussed in detail. The final part of this paper illustrates the important role of this modification in terms of the occurrence and development of colorectal cancer, cell metabolic reprogramming, and epigenetic regulation, supporting the clinical application of the use of histone lactylation as a biomarker. [ABSTRACT FROM AUTHOR]

Biosensors have emerged as a valuable tool with high specificity and sensitivity for fast and reliable detection of hazardous substances in drinking water. Numerous substances have been addressed using synthetic biology approaches. However, many proposed biosensors are based on living, genetically modified organisms and are therefore limited in shelf life, usability and biosafety. We addressed these issues by the construction of an extensible, cell-free biosensor. Storage is possible through freeze drying on paper. Following the addition of an aqueous sample, a highly efficient cell-free protein synthesis (CFPS) reaction is initiated. Specific allosteric transcription factors modulate the expression of ‘superfolder’ green fluorescent protein (sfGFP) depending on the presence of the substance of interest. The resulting fluorescence intensities are analyzed with a conventional smartphone accompanied by simple and cheap light filters. An ordinary differential equitation (ODE) model of the biosensors was developed, which enabled prediction and optimization of performance. With an optimized cell-free biosensor based on the Shigella flexneri MerR transcriptional activator, detection of 6 μg/L Hg(II) ions in water was achieved. Furthermore, a completely new biosensor for the detection of gamma-hydroxybutyrate (GHB), a substance used as date-rape drug, was established by employing the naturally occurring transcriptional repressor BlcR from Agrobacterium tumefaciens. [ABSTRACT FROM AUTHOR]

The paper mulberry is one of the multifunctional tree species in agroforestry systems and is also commonly utilized in traditional medicine in China and other Asian countries. However, little is known about its molecular genetics, which hinders research on and exploitation of this valuable resource. To discern the correlation between gene expression and the essential properties of the paper mulberry, we performed a transcriptomics analysis, assembling a total of 37,725 unigenes from 54,638,676 reads generated by RNA-seq. Among these, 22,692 unigenes showed greater than 60% similarity with genes from other species. The lengths of 13,566 annotated unigenes were longer than 1,000 bp. Functional clustering analysis with COG (Cluster of Orthologous Groups) revealed that 17,184 unigenes are primarily involved in transcription, translation, signal transduction, carbohydrate metabolism, secondary metabolism, and energy metabolism. GO (Gene Ontology) annotation suggests enrichment of genes encoding antioxidant activity, transporter activity, biosynthesis, metabolism and stress response, with a total of 30,659 unigenes falling in these categories. KEGG (Kyoto Encyclopedia of Genes and Genomes) metabolic pathway analysis showed that 7,199 unigenes are associated with 119 metabolic pathways. In addition to the basic metabolism, these genes are enriched for plant pathogen interaction, flavonoid metabolism and other secondary metabolic processes. Furthermore, differences in the transcriptomes of leaf, stem and root tissues were analyzed and 7,233 specifically expressed unigenes were identified. This global expression analysis provided novel insights about the molecular mechanisms of the biosynthesis of flavonoid, lignin and cellulose, as well as on the response to biotic and abiotic stresses including the remediation of contaminated soil by the paper mulberry. [ABSTRACT FROM AUTHOR]

Background In social groups, dominant individuals may socially inhibit reproduction of subordinates using aggressive interactions or, in the case of highly eusocial insects, pheromonal communication. It has been hypothesized these two modes of reproductive inhibition utilize conserved pathways. Here, we use a comparative framework to investigate the chemical and genomic underpinnings of reproductive dominance in the primitively eusocial wasp Polistes metricus. Our goals were to first characterize transcriptomic and chemical correlates of reproductive dominance and second, to test whether dominance-associated mechanisms in paper wasps overlapped with aggression or pheromone-related gene expression patterns in other species. To explore whether conserved molecular pathways relate to dominance, we compared wasp transcriptomic data to previous studies of gene expression associated with pheromonal communication and queen-worker differences in honey bees, and aggressive behavior in bees, Drosophila, and mice. Results By examining dominant and subordinate females from queen and worker castes in early and late season colonies, we found that cuticular hydrocarbon profiles and genome-wide patterns of brain gene expression were primarily associated with season/social environment rather than dominance status. In contrast, gene expression patterns in the ovaries were associated primarily with caste and ovary activation. Comparative analyses suggest genes identified as differentially expressed in wasp brains are not related to queen pheromonal communication or caste in bees, but were significantly more likely to be associated with aggression in other insects (bees, flies), and even a mammal (mice). Conclusions This study provides the first comprehensive chemical and molecular analysis of reproductive dominance in paper wasps. We found little evidence for a chemical basis for reproductive dominance in P. metricus, and our transcriptomic analyses suggest that different pathways regulate dominance in paper wasps and pheromone response in bees. Furthermore, there was a substantial impact of season/social environment on gene expression patterns, indicating the important role of external cues in shaping the molecular processes regulating behavior. Interestingly, genes associated with dominance in wasps were also associated with aggressive behavior in bees, solitary insects and mammals. Thus, genes involved in social regulation of reproduction in Polistes may have conserved functions associated with aggression in insects and other taxa. [ABSTRACT FROM AUTHOR]

The article cites a research study that examines the role of MiR- Par3L axis in breast cancer progression. It examined normal tissues and Par3L expressions in breast cancer tissues and cells. Par3L was found to be frequently down-regulated in human breast cancer cells and tissues and Par3L low-expression was associated with aggressive clinicopathological features and poor clinical outcome of breast cancer patients.

DNA methylation is a biochemical process that modifies gene expression without changing the underlying DNA sequence, and this represents the molecular basis for imprinting and epigenetics. Recent reports have revealed alterations in DNA methylation profiles in the placenta of babies born from assisted reproductive technologies (ART). This supports several previous observations that suggested an increase in the prevalence of imprinting diseases following ART treatment, and also fits our observations regarding the metabolism and requirements of early human embryos. Human embryo culture media (HECM) are currently formulated according to requirements based on the mouse embryo model, and in fact need to pass the Mouse Embryo Assay test in order to be accepted by the relevant authorities, despite the fact that physiological (especially the time necessary to reach genomic activation) and biochemical requirements of mouse and human embryos are quite different. This commentary aims to explain some of the discrepancies, and emphasize why human embryo metabolism tells us that the composition of HECM, as well as the role of the MEA as a unique model, should be re-evaluated. [ABSTRACT FROM AUTHOR]

Simple Summary: Neurofibromatosis Type 1 is an inherited tumour predisposition syndrome with a varied clinical phenotype. Long-term monitoring through imaging is inconsistent and varies in high- and low-income countries. Implementation of a clinical practice guideline through a multidisciplinary clinic is instrumental to the care of adult Neurofibromatosis Type 1 patients. This systematic review aims to evaluate the association between a country's socioeconomic status and diagnostic modalities and strategies used for adult Neurofibromatosis Type 1 patients. Our results show multiple imaging modalities are used in high-income countries; however, there is limited use in low-income countries. The two most common diagnostic modalities used in developed countries are WB MRI and FDG PET/CT. Background: Neurofibromatosis Type 1 is an autosomal dominant tumour-predisposition condition commonly diagnosed in childhood and fully penetrant by adulthood. Long-term monitoring through imaging is inconsistent and varies between high- and low-income countries. Implementation of a clinical practice guideline through a multidisciplinary clinic is instrumental to the care of adult Neurofibromatosis Type 1 patients. We aim to systematically review international diagnostic modalities and strategies to evaluate any association between a country's socioeconomic status and diagnostic modalities or strategies used for Neurofibromatosis Type 1 patients. Methods: We searched PubMed, Embase, Web of Science, and Cochrane. Relevant clinical information on the surveillance of adult Neurofibromatosis Type 1 patients worldwide was reviewed, extracted, and synthesised. Results: We identified 51 papers reporting on 7724 individuals. Multiple imaging modalities are actively employed in high-income and upper-middle-income countries for surveying adult Neurofibromatosis Type 1 patients. We did not find any relevant papers from low- and middle-income countries. Conclusions: This systematic review suggests that there is robust data on diagnostic modalities for adult Neurofibromatosis Type 1 patients in high-income countries, but not for low- and middle-income countries. There is a lack of data on consolidated diagnostic strategies from both high- and low-income countries. Efforts should be made to publish data on usual clinical practice in low- and middle-income countries to develop clinical practice guidelines describing best medical practice to fit a local context. [ABSTRACT FROM AUTHOR]

Gene expression is highly impacted by the environment and can be reflective of past events that affected developmental processes. It is therefore expected that gene expression can serve as a signal of a current or future phenotypic traits. In this paper we identify sets of genes, which we call Prognostic Transcriptomic Biomarkers (PTBs), that can predict firmness in Malus domestica (apple) fruits. In apples, all individuals of a cultivar are clones, and differences in fruit quality are due to the environment. The apples transcriptome responds to these differences in environment, which makes PTBs an attractive predictor of future fruit quality. PTBs have the potential to enhance supply chain efficiency, reduce crop loss, and provide higher and more consistent quality for consumers. However, several questions must be addressed. In this paper we answer the question of which of two common modeling approaches, Random Forest or ElasticNet, outperforms the other. We answer if PTBs with few genes are efficient at predicting traits. This is important because we need few genes to perform qPCR, and we answer the question if qPCR is a cost-effective assay as input for PTBs modeled using high-throughput RNA-seq. To do this, we conducted a pilot study using fruit texture in the 'Gala' variety of apples across several postharvest storage regiments. Fruit texture in 'Gala' apples is highly controllable by post-harvest treatments and is therefore a good candidate to explore the use of PTBs. We find that the RandomForest model is more consistent than an ElasticNet model and is predictive of firmness (r2 = 0.78) with as few as 15 genes. We also show that qPCR is reasonably consistent with RNA-seq in a follow up experiment. Results are promising for PTBs, yet more work is needed to ensure that PTBs are robust across various environmental conditions and storage treatments. [ABSTRACT FROM AUTHOR]

Down syndrome is a well-studied aneuploidy condition in humans, which is associated with various disease phenotypes including cardiovascular, neurological, haematological and immunological disease processes. This review paper aims to discuss the research conducted on gene expression studies during fetal development. A descriptive review was conducted, encompassing all papers published on the PubMed database between September 1960 and September 2022. We found that in amniotic fluid, certain genes such as COL6A1 and DSCR1 were found to be affected, resulting in phenotypical craniofacial changes. Additionally, other genes such as GSTT1, CLIC6, ITGB2, C21orf67, C21orf86 and RUNX1 were also identified to be affected in the amniotic fluid. In the placenta, dysregulation of genes like MEST, SNF1LK and LOX was observed, which in turn affected nervous system development. In the brain, dysregulation of genes DYRK1A, DNMT3L, DNMT3B, TBX1, olig2 and AQP4 has been shown to contribute to intellectual disability. In the cardiac tissues, dysregulated expression of genes GART, ETS2 and ERG was found to cause abnormalities. Furthermore, dysregulation of XIST, RUNX1, SON, ERG and STAT1 was observed, contributing to myeloproliferative disorders. Understanding the differential expression of genes provides insights into the genetic consequences of DS. A better understanding of these processes could potentially pave the way for the development of genetic and pharmacological therapies. [ABSTRACT FROM AUTHOR]

This document is a summary of a special issue of the International Journal of Molecular Sciences titled "The Molecular and Cellular Pathophysiologic Mechanisms Underlying Ocular Diseases and Emerging Therapies." The special issue focuses on the prevalence and rising global public health concerns of visual impairment and ophthalmic diseases. It aims to enhance researchers' and eyecare professionals' understanding of the risk factors, biomarkers, and cellular and molecular mechanisms underlying various eye diseases. The special issue includes eight papers, including original research papers, reviews, and a case report, covering topics such as diabetic retinopathy, retinal diseases, tear biomarkers, and uveal melanoma. The papers provide new advancements in the molecular and cellular pathogenesis of eye diseases and the development of preventive measures and emerging therapies. The document concludes by expressing hope that the special issue will inspire further research and understanding of eye diseases. [Extracted from the article]

Cancer is a leading cause of death globally. The majority of cancer cases are only diagnosed in the late stages of cancer due to the use of conventional methods. This reduces the chance of survival for cancer patients. Therefore, early detection consequently followed by early diagnoses are important tasks in cancer research. Gene expression microarray technology has been applied to detect and diagnose most types of cancers in their early stages and has gained encouraging results. In this paper, we address the problem of classifying cancer based on gene expression for handling the class imbalance problem and the curse of dimensionality. The oversampling technique is utilized to overcome this problem by adding synthetic samples. Another common issue related to the gene expression dataset addressed in this paper is the curse of dimensionality. This problem is addressed by applying chi-square and information gain feature selection techniques. After applying these techniques individually, we proposed a method to select the most significant genes by combining those two techniques (CHiS and IG). We investigated the effect of these techniques individually and in combination. Four benchmarking biomedical datasets (Leukemia-subtypes, Leukemia-ALLAML, Colon, and CuMiDa) were used. The experimental results reveal that the oversampling techniques improve the results in most cases. Additionally, the performance of the proposed feature selection technique outperforms individual techniques in nearly all cases. In addition, this study provides an empirical study for evaluating several oversampling techniques along with ensemble-based learning. The experimental results also reveal that SVM-SMOTE, along with the random forests classifier, achieved the highest results, with a reporting accuracy of 100%. The obtained results surpass the findings in the existing literature as well. [ABSTRACT FROM AUTHOR]

Extreme weather conditions such as heavy rainfalls have been wreaking havoc not only in urban areas but also in an entire watershed. The development of a flood management plan and flood mitigating structures to alleviate the impacts of flooding is very crucial because it needs intensive and continuous historical data. However, missing data due to equipment failure that gathers the rainfall data could be a problem. Rainfall data is not only useful in designing flood mitigating structures but also in planning our day-to-day activities ahead of time. To address this problem, this paper proposes a predictive model which able to forecast in a short lead-time and predict missing data within the dataset. In this paper, three predictive models will be compared namely recurrent neural network, Gaussian processing regression, and the proposed 6-gene genetic expression-based predictive modeling (MGGP). 29-year 24-hour cumulative rainfall data which were sourced in PAGASA Tacloban city weather station, Philippines, was used. The data were cleaned by removing negative values. Two datasets were created, the first (RFDS1) dataset which makes use of three indices (year, month, and days), and the second (RFDS2) dataset which was orchestrated and transformed to increase correlation and reduce prediction errors which had an additional two datasets (ave(t-1,t-2),t-1). Each method used three and five time-based indices. The result shows an erratic behavior of the model from three methods that used the RFDS1, while RFDS2 had a more stable predictive model. This shows that the data orchestration and transformation greatly improved the correlation and reduced errors. However, MGGP showed the best results among the three methods. [ABSTRACT FROM AUTHOR]

Simple Summary: This paper delves into the issue of metastatic endometrial cancer (EC), which significantly impacts treatment success and overall survival rates. The study explores various factors contributing to metastasis, including the molecular profile of EC, hormone activity (like estrogen and prolactin), and pro-inflammatory adipocytokines. It also investigates how altered microRNA expression affects gene regulation linked to the dissemination of the cancer. The paper highlights the importance of imaging techniques, particularly transvaginal ultrasound with tumor-free distance (uTFD), in detecting metastases. Additionally, it discusses how diagnostic and therapeutic methods can influence the spread of EC, with hysteroscopy potentially increasing risk in advanced stages and laparoscopic hysterectomy being safer if performed with care. This research could improve our understanding of EC and guide better diagnostic and treatment strategies. The presence of metastatic endometrial cancer (EC) is a key problem in treatment failure associated with reduced overall survival rates. The most common metastatic location is the pelvic lymph nodes, and the least common is the brain. The presence of metastasis depends on many factors, including the molecular profile of cancer (according to the TCGA—Genome Atlas), the activity of certain hormones (estrogen, prolactin), and pro-inflammatory adipocytokines. Additionally, an altered expression of microRNAs affecting the regulation of numerous genes is also related to the spread of cancer. This paper also discusses the value of imaging methods in detecting metastases; the primary role is attributed to the standard transvaginal USG with the tumor-free distance (uTFD) option. The influence of diagnostic and therapeutic methods on EC spread is also described. Hysteroscopy, according to the analysis discussed above, may increase the risk of metastases through a fluid medium, mainly performed in advanced stages of EC. According to another analysis, laparoscopic hysterectomy performed with particular attention to avoiding risky procedures (trocar flushing, tissue traumatization, preserving a margin of normal tissue) was not found to increase the risk of EC dissemination. [ABSTRACT FROM AUTHOR]

• Different cultivars exhibited different sensitivity to light. • Different phenolics showed different sensitivity to light. • Bagging inhibited the synthesis of most phenolics in peach fruit. • Bagging suppressed the expression of most structural genes and transcription factors. • PpHY5 homolog PpHYH was induced by high light. Bagging is a vital cultivation measure for producing high-quality peach fruit, which affects the appearance and internal quality of the fruit by mainly intervening in its exposure to light. However, it is not entirely clear whether bagging affects the content of phenolic compounds or which compounds are most sensitive to bagging treatment, and the regulatory role of bagging on phenolic synthetic-related genes is also unknown. In this experiment, four peach cultivars, 'BJ', 'XH', 'RG', and 'HYT', were bagged with four different types of bags at 50 days after full bloom, with no bag as control, and all fruits were harvested at the commercial maturation stage. The study found that bagged fruits had higher L*, b*, and h° values but lower a* and C* values than non-bagged fruits. Different cultivars and different phenolics exhibited different sensitivities to bagging treatments. Light intensity not only played a decisive role in the accumulation of anthocyanins in peach fruit but also had a strong and widespread impact on other phenolic substances. Overall, light not onlly significantly promoted the accumulation of cyanidin 3-glucoside, cyanidin 3-rutinoside, epicatechin, and rutin but also increased the accumulation of catechin, chlorogenic acid, and neochlorogenic acid to some extent, while shading by bagging inhibited the accumulation of these phenolics. Correspondingly, high light induced the upregulation of most structural genes and transcription factors, including PpPAL1, PpC3H1, PpC3H2, PpDFR, PpLDOX, PpUFGT, and PpMYB10.1 , while low light inhibited the expression of these genes in the four varieties. In addition, PpHY5 homolog PpHYH was induced by high light, which might participate in the biosynthesis of the light-regulated phenolic in peach fruit. This study lays the foundation for further analysis of the regulation mechanism of light on the synthesis of phenolic compounds in peach fruit. [ABSTRACT FROM AUTHOR]

Comparative sociogenomics has the potential to provide important insights into how social behaviour evolved. We examined brain gene expression profiles of the primitively eusocial wasp Polistes metricus and compared the results with a growing base of brain gene expression information for the advanced eusocial honeybee, Apis mellifera. We studied four female wasp groups that show variation in foraging/provisioning behaviour and reproductive status, using our newly developed microarray representing approximately 3248 P. metricus genes based on sequences generated from high-throughput pyrosequencing. We found differences in the expression of approximately 389 genes across the four groups. Pathways known from Drosophila melanogaster to be related to lipid metabolism, heat and stress response, and various forms of solitary behaviour were associated with behavioural differences among wasps. Forty-five per cent of differentially expressed transcripts showed significant associations with foraging/provisioning status, and 14 per cent with reproductive status. By comparing these two gene lists with lists of genes previously shown to be differentially expressed in association with honeybee division of labour, we found a significant overlap of genes associated with foraging/provisioning, but not reproduction, across the two species. These results suggest common molecular roots for foraging division of labour in two independently evolved social insect species and the possibility of more lineage-specific roots of reproductive behaviour. We explore the implications of these findings for the idea that there is a conserved ‘genetic toolkit’ for division of labour across multiple lineages. [ABSTRACT FROM AUTHOR]

Abstract: Dried blood spot samples (DBSS) on filter paper offer several advantages compared to conventional serum/plasma samples: they do not require any phlebotomy or separation of blood by centrifugation; they are less invasive; they allow sample stability and shipment at room temperature; and they pose a negligible risk of infection with blood-borne viruses, such as HIV, HBV and HCV, to those who handle them. Therefore dried blood spot samples (DBSS) on filter paper can be a quick, convenient and inexpensive means of obtaining blood samples for biomarker discovery, disease screening, diagnosis and treatment monitoring in non-hospitalized, public health settings. In this study, we investigated for the first time the potential application of dried blood spot samples (DBSS) in protein expression profiling using antibody array technology. First, optimal conditions for array assay performance using dried blood spot samples (DBSS) was established, including sample elution buffer, elution time, elution temperature and assay blocking buffer. Second, we analyzed dried blood spot samples (DBSS) using three distinct antibody array platforms, including sandwich-based antibody arrays, quantitative antibody arrays and biotin-label-based antibody arrays. In comparison with paired serum samples, detection of circulating proteins in dried blood spot samples (DBSS) correlated well for both low- and high-abundance proteins on all three antibody array platforms. In conclusion, our study strongly indicates the novel application of multiplex antibody array platforms to analyze dried blood spot samples (DBSS) on filter paper represents a viable, cost-effective method for protein profiling, biomarker discovery and disease screening in a large, population-based survey. [Copyright &y& Elsevier]

Gene therapy aims to modify or manipulate gene expression and change the biological characteristics of living cells to achieve the purpose of treating diseases. The safe, efficient, and stable expression of exogenous genes in cells is crucial for the success of gene therapy, which is closely related to the vectors used in gene therapy. Currently, gene therapy vectors are mainly divided into two categories: viral vectors and non-viral vectors. Viral vectors are widely used due to the advantages of persistent and stable expression, high transfection efficiency, but they also have certain issues such as infectivity, high immunological rejection, randomness of insertion mutation, carcinogenicity, and limited vector capacity. Non-viral vectors have the advantages of non-infectivity, controllable chemical structure, and unlimited vector capacity, but the transfection efficiency is low. With the rapid development of nanotechnology, the unique physicochemical properties of nanomaterials have attracted increasing attention in the field of drug and gene delivery. Among many nanomaterials, iron-based nanomaterials have attracted much attention due to their superior physicochemical properties, such as Fenton reaction, magnetic resonance imaging, magnetothermal therapy, photothermal therapy, gene delivery, magnetically-assisted drug delivery, cell and tissue targeting, and so on. In this paper, the research progress of iron-based nanomaterials in gene delivery and tumor gene therapy is reviewed, and the future application direction of iron-based nanomaterials is further prospected. [ABSTRACT FROM AUTHOR]

Simple Summary: Simple Summary: The infectious bursal disease virus (IBDV) is a major pathogen in the poultry industry due to its profound impact on the immune systems of young chickens. Various genetic types with distinct biological characteristics have been described. In this study, we evaluated the expression of different cytokines in the bursa of Fabricius and thymus over a 28-day experimental infection with two strains from the G1a (Classical) and G6 (ITA) genogroups. The G6 strain appeared to induce a more immediate immunosuppression, and unlike the G1a strain, did not show signs of gene expression recovery by the end of the study. This finding aligns with the higher replication level previously reported for the G6 and with the clinical outcome, as this genotype, although subclinical, has often been considered more immunosuppressive. Unlike other studies that focused on shorter periods post-infection, the patterns observed in this study were highly variable and complex, depending on the strain, tissue, and time point. Therefore, this study not only confirms the effect of strain/genogroup on immune system modulation but also highlights the importance of extended monitoring post-infection to better understand the intricate patterns and interactions with the host response. Infectious bursal disease virus (IBDV) is a significant burden for poultry production and market due to both direct disease and induced immunosuppression. In the present study, the expression of different cytokines in the bursa of Fabricius and thymus was evaluated during a 28-day-long experimental infection with two strains classified in the G1a (Classical) and G6 (ITA) genogroups. Although both strains significantly affected and modulated the expression of different molecules, the G6 strain seemed to induce a delayed immune response or suppress it more promptly. A recovery in the expression of several mediators was observed in the G1a-infected group at the end of the study, but not in the G6 one, further supporting a more persistent immunosuppression. This evidence fits with the higher replication level previously reported for the G6 and with the clinical outcome, as this genotype, although subclinical, has often been considered more immunosuppressive. However, unlike other studies focused on shorter time periods after infection, the patterns observed in this paper were highly variable and complex, depending on the strain, tissue, and time point, and characterized by a non-negligible within-group variability. Besides confirming the strain/genogroup effect on immune system modulation, the present study suggests the usefulness of longer monitoring activities after experimental infection to better understand the complex patterns and interactions with the host response. [ABSTRACT FROM AUTHOR]

The identification of co-regulated genes and their Transcription-Factor Binding Sites (TFBSs) are the key steps toward understanding transcription regulation. In addition to effective laboratory assays, various bi-clustering algorithms for the detection of the co-expressed genes have been developed. Bi-clustering methods are used to discover subgroups of genes with similar expression patterns under to-be-identified subsets of experimental conditions when applied to gene expression data. By building two fuzzy partition matrices of the gene expression data with the Axiomatic Fuzzy Set (AFS) theory, this paper proposes a novel fuzzy bi-clustering algorithm for the identification of co-regulated genes. Specifically, the gene expression data are transformed into two fuzzy partition matrices via the sub-preference relations theory of AFS at first. One of the matrices considers the genes as the universe and the conditions as the concept, and the other one considers the genes as the concept and the conditions as the universe. The identification of the co-regulated genes (bi-clusters) is carried out on the two partition matrices at the same time. Then, a novel fuzzy-based similarity criterion is defined based on the partition matrices, and a cyclic optimization algorithm is designed to discover the significant bi-clusters at the expression level. The above procedures guarantee that the generated bi-clusters have more significant expression values than those extracted by the traditional bi-clustering methods. Finally, the performance of the proposed method is evaluated with the performance of the three well-known bi-clustering algorithms on publicly available real microarray datasets. The experimental results are in agreement with the theoretical analysis and show that the proposed algorithm can effectively detect the co-regulated genes without any prior knowledge of the gene expression data. [ABSTRACT FROM AUTHOR]

The researches on driver pathway identification in cancer rely on traditional biological experiments, which have the drawbacks of being time-consuming, labor-intensive and costly. This paper proposed a novel binary cancer driver pathway identification method called PEA-BLMWS(parental evolutionary algorithm-binary linear maximum weight sub-matrix). Firstly, it utilized the existing gene expression data to uncovered potential gene mutation data by comparing the differences in expression levels between normal and mutated genes. Secondly, it incorporated protein-protein interaction network data to construct an improved binary linear maximum weight sub-matrix model. Finally, it proposed a parental evolutionary algorithm to solve this matrix model. Experimental results on the GBM(glioblastoma) and OVCA(ovarian cancer) datasets show that compared to other advanced identification methods such as Dendrix, CCA-NMWS and CGP-NCM, the gene set identified by PEA-BLMWS has more genes enriched in known signaling pathways, and genes not enriched in signaling pathways are also closely related to the occurrence of cancer. Therefore, this identification method can serve as an effective tool for driving pathway identification. [ABSTRACT FROM AUTHOR]

The ATP-binding cassette (ABC) transporter family is one of the largest protein families in plants and plays an essential role in addressing biotic and abiotic stresses. Wheat, a vital global grain crop, faces multifaceted safety challenges, primarily from fungal diseases like stripe rust and powdery mildew. In the present study, we identified the whole genome of the wheat ABC family, and 463 nonredundant ABC genes were identified. The ABC family can be divided into nine evolutionary branches and eight subfamilies based on phylogenetic tree analysis. This paper delved deeper into characterizing the gene structure, promoter region, and gene expression within the TaABC family. Segmental duplication was the main reason for the expansion of the TaABC genes. Ka/Ks analysis suggested that most TaABC genes were intensely purified and selected. The collinear analysis of TaABC and other species showed that the ABC genes were conserved in evolution. RNA-seq data and qPCR data from wheat infected with powdery mildew or stripe rust showed that most TaABC genes were induced to change expression. The candidate genes TaABCB15-3B and TaABCG38 exhibited responsiveness to powdery mildew in resistant/susceptible wheat, while remaining unresponsive to stripe rust. Our findings serve as a valuable reference for gaining a deeper understanding of the function and evolution of TaABCs, aiding in the identification of enduring disease resistance genes within the TaABCs of wheat. [ABSTRACT FROM AUTHOR]

• This paper proposed an enet-regularization negative binomial regression model (called m6Aexpress-enet) to predict which m6A site could potentially regulate its gene expression. • m6Aexpress-enet could achieve higher prediction performance by reducing the influence of the multicollinearity problem caused by the correlation of methylation level of multiple m6A sites in each gene. • Applying m6Aexpress-enet on MeRIP-seq data from human lymphoblastoid cell lines, we have uncovered the complex regulatory pattern of predicted m6A sites and their unique enrichment pathway of the constructed co-methylation modules. As the most abundant mRNA modification, m6A controls and influences many aspects of mRNA metabolism including the mRNA stability and degradation. However, the role of specific m6A sites in regulating gene expression still remains unclear. In additional, the multicollinearity problem caused by the correlation of methylation level of multiple m6A sites in each gene could influence the prediction performance. To address the above challenges, we propose an elastic-net regularized negative binomial regression model (called m6Aexpress-enet) to predict which m6A site could potentially regulate its gene expression. Comprehensive evaluations on simulated datasets demonstrate that m6Aexpress-enet could achieve the top prediction performance. Applying m6Aexpress-enet on real MeRIP-seq data from human lymphoblastoid cell lines, we have uncovered the complex regulatory pattern of predicted m6A sites and their unique enrichment pathway of the constructed co-methylation modules. m6Aexpress-enet proves itself as a powerful tool to enable biologists to discover the mechanism of m6A regulatory gene expression. Furthermore, the source code and the step-by-step implementation of m6Aexpress-enet is freely accessed at https://github.com/tengzhangs/m6Aexpress-enet. [ABSTRACT FROM AUTHOR]

The advance of high-throughput biomedical technology makes it possible to access massive measurements of gene expression levels. An important statistical issue is identifying both under-expressed and over-expressed genes for a disease. Most existing multiple-testing procedures focus on selecting only the non-null or significant genes without further identifying their expression type. Only limited methods are designed for the directional problem, and yet they fail to separately control the numbers of falsely discovered over-expressed and under-expressed genes with only a unified index combining all the false discoveries. In this paper, based on a three-classification multiple testing framework, we propose a practical data-driven procedure to control separately the two directions of false discoveries. The proposed procedure is theoretically valid and optimal in the sense that it maximizes the expected number of true discoveries while controlling the false discovery rates for under-expressed and over-expressed genes simultaneously. The procedure allows different nominal levels for the two directions, exhibiting high flexibility in practice. Extensive numerical results and analysis of two large-scale genomic datasets show the effectiveness of our procedure. [ABSTRACT FROM AUTHOR]

Coffin-Siris syndrome (CSS) is a rare autosomal dominant inheritance disorder characterized by distinctive facial features, hypoplasia of the distal phalanx or nail of the fifth and additional digits, developmental or cognitive delay of varying degree, hypotonia, hirsutism/hypertrichosis, sparse scalp hair and varying kind of congenital anomalies. CSS can easily be misdiagnosed as other syndromes or disorders with a similar clinical picture because of their genetic and phenotypic heterogeneity. We describde the genotype-phenotype correlation of one patient from a healthy Chinese family with a novel genotype underlying CSS, who was first diagnosed in the ophthalmology department as early-onset high myopia (eoHM). Comprehensive ophthalmic tests as well as other systemic examinations were performed on participants to confirm the phenotype. The genotype was identified using whole exome sequencing, and further verified the results among other family members by Sanger sequencing. Real-time quantitative PCR (RT-qPCR) technology was used to detect the relative mRNA expression levels of candidate genes between proband and normal family members. The pathogenicity of the identified variant was determined by The American College of Medical Genetics and Genomics (ACMG) guidelines. STRING protein-protein interactions (PPIs) network analysis was used to detect the interaction of candidate gene-related proteins with high myopia gene-related proteins. The patient had excessive eoHM, cone-rod dystrophy, coarse face, excessive hair growth on the face, sparse scalp hair, developmental delay, intellectual disability, moderate hearing loss, dental hypoplasia, patent foramen ovale, chronic non-atrophic gastritis, bilateral renal cysts, cisterna magna, and emotional outbursts with aggression. The genetic assessment revealed that the patient carries a de novo heterozygous frameshift insertion variant in the ARID1B c.3981dup (p.Glu1328ArgfsTer5), which are strongly associated with the typical clinical features of CSS patients. The test results of RT-qPCR showed that mRNA expression of the ARID1B gene in the proband was approximately 30% lower than that of the normal control in the family, suggesting that the variant had an impact on the gene function at the level of mRNA expression. The variant was pathogenic as assessed by ACMG guidelines. Analysis of protein interactions in the STRING online database revealed that the ARID1A protein interacts with the high myopia gene-related proteins FGFR3, ASXL1, ERBB3, and SOX4, whereas the ARID1A protein antagonizes the ARID1B protein. Therefore, in this paper, we are the first to report a de novo heterozygous frameshift insertion variant in the ARID1B gene causing CSS with excessive eoHM. Our study extends the genotypic and phenotypic spectrums for ARID1B-CSS and supplies evidence of significant association of eoHM with variant in ARID1B gene. As CSS has high genetic and phenotypic heterogeneity, our findings highlight the importance of molecular genetic testing and an interdisciplinary clinical diagnostic workup to avoid misdiagnosis as some disorders with similar manifestations of CSS. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of altering the protein expression dynamics of the bHLH transcription factor Her6 at the single-cell level in the embryonic zebrafish telencephalon. Using a homozygote endogenous Her6:Venus reporter and 4D single-cell tracking, we show that Her6 oscillates in neural telencephalic progenitors and that the fusion of protein destabilisation (PEST) domain alters its expression dynamics, causing most cells to downregulate Her6 prematurely. However, counterintuitively, oscillatory cells increase, with some expressing Her6 at high levels, resulting in increased heterogeneity of Her6 expression in the population. These tissuelevel changes appear to be an emergent property of coupling between single-cells, as revealed by experimentally disrupting Notch signalling and by computationally modelling alterations in Her6 protein stability. Despite the profound differences in the single-cell Her6 dynamics, the size of the telencephalon is only transiently altered and differentiation markers do not exhibit significant differences early on; however, a small increase is observed at later developmental stages. Our study suggests that cell coupling provides a compensation strategy, whereby an almost normal phenotype is maintained even though single-cell gene expression dynamics are abnormal, granting phenotypic robustness. [ABSTRACT FROM AUTHOR]

In experiments, the distributions of mRNA or protein numbers in single cells are often fitted to the random telegraph model which includes synthesis and decay of mRNA or protein, and switching of the gene between active and inactive states. While commonly used, this model does not describe how fluctuations are influenced by crucial biological mechanisms such as feedback regulation, non-exponential gene inactivation durations, and multiple gene activation pathways. Here we investigate the dynamical properties of four relatively complex gene expression models by fitting their steady-state mRNA or protein number distributions to the simple telegraph model. We show that despite the underlying complex biological mechanisms, the telegraph model with three effective parameters can accurately capture the steady-state gene product distributions, as well as the conditional distributions in the active gene state, of the complex models. Some effective parameters are reliable and can reflect realistic dynamic behaviors of the complex models, while others may deviate significantly from their real values in the complex models. The effective parameters can also be applied to characterize the capability for a complex model to exhibit multimodality. Using additional information such as single-cell data at multiple time points, we provide an effective method of distinguishing the complex models from the telegraph model. Furthermore, using measurements under varying experimental conditions, we show that fitting the mRNA or protein number distributions to the telegraph model may even reveal the underlying gene regulation mechanisms of the complex models. The effectiveness of these methods is confirmed by analysis of single-cell data for E. coli and mammalian cells. All these results are robust with respect to cooperative transcriptional regulation and extrinsic noise. In particular, we find that faster relaxation speed to the steady state results in more precise parameter inference under large extrinsic noise. Author summary: Over the past decade, significant progress has been made in the theory and experiments of single-cell stochastic gene expression dynamics. The most well studied and widely used stochastic gene expression model is the two-state telegraph model. However, the conventional telegraph model is too simple and limited in its predictive power because it lacks a description of some important biological mechanisms, such as feedback regulation, multiple gene activation steps, and multiple gene activation pathways. This raises a important question: what can we learn when fitting a complex gene expression model to a simple telegraph model? In this paper, we investigate four complex gene expression models by fitting their steady-state mRNA or protein number distributions to the telegraph model and then obtain estimates of the effective parameters. We show that while the estimated values of the parameters in the "artificial" telegraph model are not always accurate, they are still sometimes reliable and can also reveal important dynamical properties of the complex models such as the ability for a complex model to produce bimodality. Moreover, we provide an effective method of distinguishing the complex models from the telegraph model by using additional information such as gene expression data at multiple time points. Finally, we show that fitting the mRNA or protein number distributions to the telegraph model may even reveal the underlying gene regulation mechanism of a complex model by using measurements under varying experimental conditions. The effectiveness of these methods is well confirmed by analysis of single-cell gene expression data for E. coli and mammalian cells. [ABSTRACT FROM AUTHOR]

XTH genes are key genes that regulate the hydrolysis and recombination of XG components and plays role in the structure and composition of plant cell walls. Therefore, clarifying the changes that occur in XTHs during plant defense against abiotic stresses is informative for the study of the plant stress regulatory mechanism mediated by plant cell wall signals. XTH proteins in Arabidopsis thaliana was selected as the seed sequences in combination with its protein structural domains, 80 members of the BnXTH gene family were jointly identified from the whole genome of the Brassica napus ZS11, and analyzed for their encoded protein physicochemical properties, phylogenetic relationships, covariance relationships, and interoperating miRNAs. Based on the transcriptome data, the expression patterns of BnXTHs were analyzed in response to different abiotic stress treatments. The relative expression levels of some BnXTH genes under Al, alkali, salt, and drought treatments after 0, 6, 12 and 24 h were analyzed by using qRT-PCR to explore their roles in abiotic stress tolerance in B. napus. BnXTHs showed different expression patterns in response to different abiotic stress signals, indicating that the response mechanisms of oilseed rape against different abiotic stresses are also different. This paper provides a theoretical basis for clarifying the function and molecular genetic mechanism of the BnXTH gene family in abiotic stress tolerance in rapeseed. [ABSTRACT FROM AUTHOR]

Simple Summary: Metastatic breast cancer is an aggressive disease that early diagnostic attempts is of an utmost importance. A machine learning model that utilizes NCA and MRMR in this work is attempting to isolate pertinent dysregulated miRNA's for the different four cancer stages. This work compares the current clinical diagnostic approaches with the proposed ML model results. Determining the tumor origin in humans is vital in clinical applications of molecular diagnostics. Metastatic cancer is usually a very aggressive disease with limited diagnostic procedures, despite the fact that many protocols have been evaluated for their effectiveness in prognostication. Research has shown that dysregulation in miRNAs (a class of non-coding, regulatory RNAs) is remarkably involved in oncogenic conditions. This research paper aims to develop a machine learning model that processes an array of miRNAs in 1097 metastatic tissue samples from patients who suffered from various stages of breast cancer. The suggested machine learning model is fed with miRNA quantitative read count data taken from The Cancer Genome Atlas Data Repository. Two main feature-selection techniques have been used, mainly Neighborhood Component Analysis and Minimum Redundancy Maximum Relevance, to identify the most discriminant and relevant miRNAs for their up-regulated and down-regulated states. These miRNAs are then validated as biological identifiers for each of the four cancer stages in breast tumors. Both machine learning algorithms yield performance scores that are significantly higher than the traditional fold-change approach, particularly in earlier stages of cancer, with Neighborhood Component Analysis and Minimum Redundancy Maximum Relevance achieving accuracy scores of up to 0.983 and 0.931, respectively, compared to 0.920 for the FC method. This study underscores the potential of advanced feature-selection methods in enhancing the accuracy of cancer stage identification, paving the way for improved diagnostic and therapeutic strategies in oncology. [ABSTRACT FROM AUTHOR]

The heterogeneity of Hepatocellular Carcinoma (HCC) poses a barrier to effective treatment. Stratifying highly heterogeneous HCC into molecular subtypes with similar features is crucial for personalized anti-tumor therapies. Although driver genes play pivotal roles in cancer progression, their potential in HCC subtyping has been largely overlooked. This study aims to utilize driver genes to construct HCC subtype models and unravel their molecular mechanisms. Utilizing a novel computational framework, we expanded the initially identified 96 driver genes to 1192 based on mutational aspects and an additional 233 considering driver dysregulation. These genes were subsequently employed as stratification markers for further analyses. A novel multi-omics subtype classification algorithm was developed, leveraging mutation and expression data of the identified stratification genes. This algorithm successfully categorized HCC into two distinct subtypes, CLASS A and CLASS B, demonstrating significant differences in survival outcomes. Integrating multi-omics and single-cell data unveiled substantial distinctions between these subtypes regarding transcriptomics, mutations, copy number variations, and epigenomics. Moreover, our prognostic model exhibited excellent predictive performance in training and external validation cohorts. Finally, a 10-gene classification model for these subtypes identified TTK as a promising therapeutic target with robust classification capabilities. This comprehensive study provides a novel perspective on HCC stratification, offering crucial insights for a deeper understanding of its pathogenesis and the development of promising treatment strategies. Author summary: Dividing highly heterogeneous HCC into molecular subtypes with similar characteristics is crucial for personalized anti-tumor therapies. Although driver genes play pivotal roles in cancer progression, their potential in HCC subtyping has been largely overlooked. In this work, we developed a multi-omics network-based stratification algorithm that utilizes patient mutation data and requires smaller computational resources for subtype assignment. Through this algorithm, we categorized HCC into two subtypes, CLASS A and CLASS B. Using multi-omics and single-cell data, we identified differences between these subtypes in gene expression, methylation, immune infiltration, and other aspects. Beyond subtype characterization, our study established a robust clinical prediction model (https://mike-wang-bjut.shinyapps.io/DynNomapp%5fHCC%5fSutypes/) incorporating subtype information and typical clinical features, enabling precise survival predictions. Finally, we developed a high-performing machine learning classifier for our subtype. Analyzing this classification model and reviewing previous experimental papers, we identified TTK as a potential diagnostic marker and therapeutic target specific to our subtypes. In conclusion, our research offers a novel perspective on HCC stratification, which is crucial for a deeper understanding of its pathogenesis and developing promising treatment strategies. [ABSTRACT FROM AUTHOR]

Background: Multiple studies have demonstrated a negative correlation between gene expression and positioning of genes at the nuclear envelope (NE) lined by nuclear lamina, but the exact relationship remains unclear, especially in light of the highly stochastic, transient nature of the gene association with the NE. Results: In this paper, we ask whether there is a causal, systematic, genome-wide relationship between the expression levels of the groups of genes in topologically associating domains (TADs) of Drosophila nuclei and the probabilities of TADs to be found at the NE. To investigate the nature of this possible relationship, we combine a coarse-grained dynamic model of the entire Drosophila nucleus with genome-wide gene expression data; we analyze the TAD averaged transcription levels of genes against the probabilities of individual TADs to be in contact with the NE in the control and lamins-depleted nuclei. Our findings demonstrate that, within the statistical error margin, the stochastic positioning of Drosophila melanogaster TADs at the NE does not, by itself, systematically affect the mean level of gene expression in these TADs, while the expected negative correlation is confirmed. The correlation is weak and disappears completely for TADs not containing lamina-associated domains (LADs) or TADs containing LADs, considered separately. Verifiable hypotheses regarding the underlying mechanism for the presence of the correlation without causality are discussed. These include the possibility that the epigenetic marks and affinity to the NE of a TAD are determined by various non-mutually exclusive mechanisms and remain relatively stable during interphase. Conclusions: At the level of TADs, the probability of chromatin being in contact with the nuclear envelope has no systematic, causal effect on the transcription level in Drosophila. The conclusion is reached by combining model-derived time-evolution of TAD locations within the nucleus with their experimental gene expression levels. [ABSTRACT FROM AUTHOR]

Finding out how diet impacts health and metabolism while concentrating on the functional qualities and bioactive components of food is the crucial scientific objective of nutritional research. The complex relationship between metabolism and nutrition could be investigated with cutting-edge "omics" and bioinformatics techniques. This review paper provides an overview of the use of omics technologies in nutritional research, with a particular emphasis on the new applications of transcriptomics, proteomics, metabolomics, and genomes in functional and biological activity research on ruminant livestock and products in the tropical regions. A wealth of knowledge has been uncovered regarding the regulation and use of numerous physiological and pathological processes by gene, mRNA, protein, and metabolite expressions under various physiological situations and guidelines. In particular, the components of meat and milk were assessed using omics research utilizing the various methods of transcriptomics, proteomics, metabolomics, and genomes. The goal of this review is to use omics technologies—which have been steadily gaining popularity as technological tools—to develop new nutritional, genetic, and leadership strategies to improve animal products and their quality control. We also present an overview of the new applications of omics technologies in cattle production and employ nutriomics and foodomics technologies to investigate the microbes in the rumen ecology. Thus, the application of state-of-the-art omics technology may aid in our understanding of how species and/or breeds adapt, and the sustainability of tropical animal production, in the long run, is becoming increasingly important as a means of mitigating the consequences of climate change. [ABSTRACT FROM AUTHOR]

Microbial electrosynthesis (MES) is a promising technology that mainly utilizes microbial cells to convert CO2 into value-added chemicals using electrons provided by the cathode. However, the low electron transfer rate is a solid bottleneck hindering the further application of MES. Thus, as an effective strategy, genetic tools play a key role in MES for enhancing the electron transfer rate and diversity of production. We describe a set of genetic strategies based on fundamental characteristics and current successes and discuss their functional mechanisms in driving microbial electrocatalytic reactions to fully comprehend the roles and uses of genetic tools in MES. This paper also analyzes the process of nanomaterial application in extracellular electron transfer (EET). It provides a technique that combines nanomaterials and genetic tools to increase MES efficiency, because nanoparticles have a role in the production of functional genes in EET although genetic tools can subvert MES, it still has issues with difficult transformation and low expression levels. Genetic tools remain one of the most promising future strategies for advancing the MES process despite these challenges. [ABSTRACT FROM AUTHOR]

The penalized Lasso Cox proportional hazards model has been widely used to identify prognosis biomarkers in high-dimension settings. However, this method tends to select many false positives, affecting its interpretability. In order to improve the reproducibility, we develop a knockoff procedure that consists on wrapping the Lasso Cox model with the model-X knockoff, resulting in a powerful tool for variable selection that allows for the control of the false discovery rate in the presence of finite sample guarantees. In this paper, we propose a novel approach to sample valid knockoffs for ordinal and continuous variables whose distributions can be skewed or heavy-tailed, which employs a Latent Mixed Gaussian Copula model to account for the dependence structure between the variables, leading to what we call the Latent Gaussian Copula Knockoff (LGCK) procedure. We then combine the LGCK method with the Lasso coefficient difference (LCD) statistic as the importance metric. To our knowledge, our proposal is the first knockoff framework for jointly considering ordinal and continuous data in a non-Gaussian setting and a survival context. We illustrate the proposed methodology's effectiveness by applying it to a real lung cancer gene expression dataset. [ABSTRACT FROM AUTHOR]

The massive amount of human biological, imaging, and clinical data produced by multiple and diverse sources necessitates integrative modeling approaches able to summarize all this information into answers to specific clinical questions. In this paper, we present a hypermodeling scheme able to combine models of diverse cancer aspects regardless of their underlying method or scale. Describing tissue-scale cancer cell proliferation, biomechanical tumor growth, nutrient transport, genomic-scale aberrant cancer cell metabolism, and cell-signaling pathways that regulate the cellular response to therapy, the hypermodel integrates mutation, miRNA expression, imaging, and clinical data. The constituting hypomodels, as well as their orchestration and links, are described. Two specific cancer types, Wilms tumor (nephroblastoma) and non-small cell lung cancer, are addressed as proof-of-concept study cases. Personalized simulations of the actual anatomy of a patient have been conducted. The hypermodel has also been applied to predict tumor control after radiotherapy and the relationship between tumor proliferative activity and response to neoadjuvant chemotherapy. Our innovative hypermodel holds promise as a digital twin-based clinical decision support system and as the core of future in silico trial platforms, although additional retrospective adaptation and validation are necessary. [ABSTRACT FROM AUTHOR]

Advancements in the field of next generation sequencing (NGS) have generated vast amounts of data for the same set of subjects. The challenge that arises is how to combine and reconcile results from different omics studies, such as epigenome and transcriptome, to improve the classification of disease subtypes. In this study, we introduce sCClust (sparse canonical correlation analysis with clustering), a technique to combine high-dimensional omics data using sparse canonical correlation analysis (sCCA), such that the correlation between datasets is maximized. This stage is followed by clustering the integrated data in a lower-dimensional space. We apply sCClust to gene expression and DNA methylation data for three cancer genomics datasets from the Cancer Genome Atlas (TCGA) to distinguish between underlying subtypes. We evaluate the identified subtypes using Kaplan–Meier plots and hazard ratio analysis on the three types of cancer—GBM (glioblastoma multiform), lung cancer and colon cancer. Comparison with subtypes identified by both single- and multi-omics studies implies improved clinical association. We also perform pathway over-representation analysis in order to identify up-regulated and down-regulated genes as tentative drug targets. The main goal of the paper is twofold: the integration of epigenomic and transcriptomic datasets followed by elucidating subtypes in the latent space. The significance of this study lies in the enhanced categorization of cancer data, which is crucial to precision medicine. [ABSTRACT FROM AUTHOR]

Transcriptional cis-regulatory modules, e.g., enhancers, control the time and location of metazoan gene expression. While changes in enhancers can provide a powerful force for evolution, there is also significant deep conservation of enhancers for developmentally important genes, with function and sequence characteristics maintained over hundreds of millions of years of divergence. Not well understood, however, is how the overall regulatory composition of a locus evolves, with important outstanding questions such as how many enhancers are conserved vs. novel, and to what extent are the locations of conserved enhancers within a locus maintained? We begin here to address these questions with a comparison of the respective single-minded (sim) loci in the two dipteran species Drosophila melanogaster (fruit fly) and Aedes aegypti (mosquito). sim encodes a highly conserved transcription factor that mediates development of the arthropod embryonic ventral midline. We identify two enhancers in the A. aegypti sim locus and demonstrate that they function equivalently in both transgenic flies and transgenic mosquitoes. One A. aegypti enhancer is highly similar to known Drosophila counterparts in its activity, location, and autoregulatory capability. The other differs from any known Drosophila sim enhancers with a novel location, failure to autoregulate, and regulation of expression in a unique subset of midline cells. Our results suggest that the conserved pattern of sim expression in the two species is the result of both conserved and novel regulatory sequences. Further examination of this locus will help to illuminate how the overall regulatory landscape of a conserved developmental gene evolves. Author summary: The expression patterns and roles of genes, especially those involved in core developmental processes, are often conserved over vast evolutionary distances. Paradoxically, the DNA sequences surrounding these genes, which contain the cis-regulatory sequences (enhancers) that regulate gene expression, tend to be highly diverged. The manner and extent to which enhancers are functionally conserved, and how the overall organization of regulatory sequences within a locus is preserved or restructured, is not well understood. In this paper, we investigate these questions by identifying enhancers controlling expression of a master nervous system regulatory gene named sim in the mosquito Aedes aegypti, and comparing their functions and locations to those in the well-characterized sim locus of the fruit fly Drosophila melanogaster. Our results suggest that the two species generate identical patterns of sim expression through a mix of conserved and novel regulatory sequences. Continued exploration of the sim locus in these two species will help to build a comprehensive picture of how a regulatory locus for a master developmental regulator has evolved. [ABSTRACT FROM AUTHOR]